Noise-correlation spectrum for a pair of spin qubits in silicon

• Published in: Nature physics 2023-12, Vol.19 (12), p.1793-1798
• Main Authors: Yoneda, J., Rojas-Arias, J. S., Stano, P., Takeda, K., Noiri, A., Nakajima, T., Loss, D., Tarucha, S.
• Format: Article
• Language: English
• Subjects: 639/766/483/2802; 639/925/927/481; Atomic; Classical and Continuum Physics; Complex Systems; Condensed Matter Physics; Cross correlation; Electric fields; Electric noise; Errors; Fault tolerance; Fluctuations; Mathematical and Computational Physics; Molecular; Noise; Optical and Plasma Physics; Physics; Physics and Astronomy; Quantum computers; Qubits (quantum computing); Silicon; Spin exchange; Theoretical
• ISSN: 1745-2473; 1745-2481
• DOI: 10.1038/s41567-023-02238-6

Semiconductor qubits have a small footprint and so are appealing for building densely integrated quantum processors. However, fabricating them at high densities raises the issue of noise correlated across different qubits, which is of practical concern for scalability and fault tolerance. Here, we analyse and quantify the degree of noise correlation in a pair of neighbouring silicon spin qubits around 100 nm apart. We observe strong interqubit noise correlations with a correlation strength as large as 0.7 at around 1 Hz, even in the regime where the spin–spin exchange interaction contributes negligibly. We find that fluctuations of single-spin precession rates are strongly correlated with exchange noise, showing that they have an electrical origin. Noise cross-correlations have thus enabled us to pinpoint the most influential noise in our device. Our work presents a powerful tool set to assess and identify the noise acting on multiple qubits and highlights the importance of long-range electric noise in densely packed silicon spin qubits. Errors in a quantum computer that are correlated between different qubits pose a considerable challenge for correction schemes. Measurements of noise in silicon spin qubits show that electric field fluctuations can create strongly correlated errors.